The first principle quantum chemistry methods are widely used in molecular modeling studies in biology, chemistry and material science. Among the quantum chemistry models, density functional theory (DFT) offers a right balance between computational cost and accuracy and accounts for the majority use in biological researches. In this project, we are proposing a technology that is aimed at reducing significantly the computational cost of the evaluation of the exchange-correlation contribution, which is the most time consuming step in a DFT calculation. This technology is to take the advantage of the nature of the iteration process of the DFT calculation and computes the desired quantities through the differences of variables between iterations. In this Phase I feasibility study the goal is to develop the algorithm for the basic local functionals with closed-shell systems. The potentials & problems will be identified for the further studies in Phase II, in which the technology will be implemented for gradient-corrected functionals with closed-shell and open-shell systems. If successful, this improvement will substantially enhance the productivity of computational researches, and enable researchers to study larger systems with the same amount of computational cost. PROPOSED COMMERCIAL APPLICATIONS: DFT is the most widely used quantum chemistry model in computational researches. The success of this project will enhance significantly the productivity and efficiency of molecular modeling researches at universities and industrial, governmental research facilities.